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Resource allocation for performance improvement

Author

Listed:
  • Nasim Nasrabadi
  • Akram Dehnokhalaji
  • Narsis Kiani
  • Pekka Korhonen
  • Jyrki Wallenius

Abstract

In this paper the problem of allocating resources among Decision Making Units is considered. This study covers the case in which several homogeneous units are operating under the supervision of a central unit. The resource allocation is carried out by the DM (central unit) in such a way that the overall performance of the system is improved. Performance is defined by means of a convex combination of the ratio of the efficiencies before and after the resource allocation. It is assumed that each unit is allowed to modify its resources within the current production possibility set. A novel model is proposed which aims at achieving the best performance of the system. The method is capable of dealing with some additional constraints, imposed by the DM. The model is illustrated by a simple numerical example and a real application. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Nasim Nasrabadi & Akram Dehnokhalaji & Narsis Kiani & Pekka Korhonen & Jyrki Wallenius, 2012. "Resource allocation for performance improvement," Annals of Operations Research, Springer, vol. 196(1), pages 459-468, July.
    • Handle: RePEc:spr:annopr:v:196:y:2012:i:1:p:459-468:10.1007/s10479-011-1016-y
    DOI: 10.1007/s10479-011-1016-y
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    References listed on IDEAS

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    Cited by:

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    3. Menghan Chen & Sheng Ang & Lijing Jiang & Feng Yang, 2020. "Centralized resource allocation based on cross-evaluation considering organizational objective and individual preferences," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(2), pages 529-565, June.
    4. Akram Dehnokhalaji & Mojtaba Ghiyasi & Pekka Korhonen, 2017. "Resource allocation based on cost efficiency," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1279-1289, October.
    5. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2014. "Optimal profits under environmental regulation: The benefits from emission intensity averaging," Darmstadt Discussion Papers in Economics 220, Darmstadt University of Technology, Department of Law and Economics.
    6. Benjamin Hampf & Kenneth Løvold Rødseth, 2017. "Optimal profits under environmental regulation: the benefits from emission intensity averaging," Annals of Operations Research, Springer, vol. 255(1), pages 367-390, August.
    7. Vincent Mousseau & Özgür Özpeynirci & Selin Özpeynirci, 2018. "Inverse multiple criteria sorting problem," Annals of Operations Research, Springer, vol. 267(1), pages 379-412, August.
    8. Contreras, I. & Lozano, S., 2020. "Allocating additional resources to public universities. A DEA bargaining approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    9. Lozano, Sebastián & Contreras, Ignacio, 2022. "Centralised resource allocation using Lexicographic Goal Programming. Application to the Spanish public university system," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    10. Yong-Wu Zhou & Chuanying Chen & Yuanguang Zhong & Bin Cao, 2020. "The allocation optimization of promotion budget and traffic volume for an online flash-sales platform," Annals of Operations Research, Springer, vol. 291(1), pages 1183-1207, August.
    11. Afsharian, Mohsen & Ahn, Heinz & Harms, Sören Guntram, 2021. "A review of DEA approaches applying a common set of weights: The perspective of centralized management," European Journal of Operational Research, Elsevier, vol. 294(1), pages 3-15.
    12. Liesiö, Juuso & Andelmin, Juho & Salo, Ahti, 2020. "Efficient allocation of resources to a portfolio of decision making units," European Journal of Operational Research, Elsevier, vol. 286(2), pages 619-636.

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